Domestic violence is associated with environmental suppression of IQ in young children

2003 ◽  
Vol 15 (2) ◽  
pp. 297-311 ◽  
Author(s):  
KARESTAN C. KOENEN ◽  
TERRIE E. MOFFITT ◽  
AVSHALOM CASPI ◽  
ALAN TAYLOR ◽  
SHAUN PURCELL
Keyword(s):  
Domestic Violence ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Population Sample ◽  
Animal Experiments ◽  
Ordinary Least Squares ◽  
Genetic Influences ◽  
Least Squares Regression ◽  
Extreme Stress ◽  
Lower Intelligence

Research suggests that exposure to extreme stress in childhood, such as domestic violence, affects children's neurocognitive development, leading to lower intelligence. But studies have been unable to account for genetic influences that might confound the association between domestic violence and lower intelligence. This twin study tested whether domestic violence had environmentally mediated effects on young children's intelligence. Children's IQs were assessed for a population sample of 1116 monozygotic and dizygotic 5-year-old twin pairs in England. Mothers reported their experience of domestic violence in the previous 5 years. Ordinary least squares regression showed that domestic violence was uniquely associated with IQ suppression in a dose–response relationship. Children exposed to high levels of domestic violence had IQs that were, on average, 8 points lower than unexposed children. Structural equation models showed that adult domestic violence accounted for 4% of the variation, on average, in child IQ, independent of latent genetic influences. The findings are consistent with animal experiments and human correlational studies documenting the harmful effects of extreme stress on brain development. Programs that successfully reduce domestic violence should also have beneficial effects on children's cognitive development.

scholarly journals Correcting measurement error bias in interaction models with small samples

2006 ◽  
Vol 3 (2) ◽  
Author(s):  
Josep Bisbe ◽  
Germà Coenders ◽  
Willem Saris ◽  
Joan Batista-Foguet
Keyword(s):  
Measurement Error ◽  
Least Squares ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Ordinary Least Squares ◽  
Alternative Methods ◽  
Small Samples ◽  
Least Squares Regression ◽  
Interaction Terms ◽  
Error Bias

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression.

The Differential Heritability of Regular Tobacco Use Based on Method of Administration

2005 ◽  
Vol 8 (1) ◽  
pp. 60-62 ◽  
Author(s):  
J. Eric Schmitt ◽  
Carol A. Prescott ◽  
Charles O. Gardner ◽  
Michael C. Neale ◽  
Kenneth S. Kendler
Keyword(s):  
Tobacco Use ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Genetic Influences ◽  
Shared Environment ◽  
Chewing Tobacco ◽  
Differential Heritability ◽  
Moist Snuff ◽  
Twin Resemblance

AbstractSeveral large studies have demonstrated that the liability to smoke cigarettes is strongly genetically influenced. However, the role of genetic and environmental risk factors in the use of other common forms of tobacco use has yet to be studied. Data on the regular use of cigarettes, cigars, pipes, dip (moist snuff), and chewing tobacco from 2634 male twins were analyzed with ACE structural equation models. Twin similarity for regular cigarette and dip use was largely genetic in origin. However, twin resemblance for chewing tobacco was just about equally the result of genes and shared environment, and twin similarity for use of pipes and cigars was entirely the result of shared environmental factors. Thus, the genetic influences on the liability for regular tobacco use appear to vary based on tobacco type. The causes for the use of different forms of tobacco are complex and worthy of further study.

scholarly journals Separation of genetic influences on attention deficit hyperactivity disorder symptoms and reaction time performance from those on IQ

2009 ◽  
Vol 40 (6) ◽  
pp. 1027-1037 ◽  
Author(s):  
A. C. Wood ◽  
P. Asherson ◽  
J. J. van der Meere ◽  
J. Kuntsi
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Reaction Time ◽  
Attention Deficit ◽  
Adhd Symptom ◽  
Structural Equation ◽  
Population Sample ◽  
Genetic Influences ◽  
Hyperactivity Disorder ◽  
Symptom Scores ◽  
Shared Genetic

BackgroundAttention deficit hyperactivity disorder (ADHD) shows a strong phenotypic and genetic association with reaction time (RT) variability, considered to reflect lapses in attention. Yet we know little about whether this aetiological pathway is shared with other affected cognitive processes in ADHD, such as lower IQs or the generally slower responses (mean RTs). We aimed to address the question of whether a shared set of genes exist that influence RT variability, mean RT, IQ and ADHD symptom scores, or whether there is evidence of separate aetiological pathways.MethodMultivariate structural equation modelling on cognitive tasks data (providing RT data), IQ and ADHD ratings by parents and teachers collected on general population sample of 1314 twins, at ages 7–10 years.ResultsMultivariate structural equation models indicated that the shared genetic influences underlying both ADHD symptom scores and RT variability are also shared with those underlying mean RT, with both types of RT data largely indexing the same underlying liability. By contrast, the shared genetic influences on ADHD symptom scores and RT variability (or mean RT) are largely independent of the genetic influences that ADHD symptom scores share with IQ.ConclusionsThe finding of unique aetiological pathways between IQ and RT data, but shared components between mean RT, RT variability and ADHD symptom scores, illustrates key influences in the genetic architecture of the cognitive and energetic processes that underlie the behavioural symptoms of ADHD. In addition, the multivariate genetic model fitting findings provide valuable information for future molecular genetic analyses.

scholarly journals The amplification of genetic factors for early vocabulary during children’s language and literacy development

2019 ◽  
Author(s):  
Ellen Verhoef ◽  
Chin Yang Shapland ◽  
Simon E. Fisher ◽  
Philip S. Dale ◽  
Beate St Pourcain
Keyword(s):  
Cognitive Skills ◽  
Structural Equation ◽  
Genetic Factors ◽  
Structural Equation Models ◽  
Receptive Language ◽  
Literacy Skills ◽  
Receptive Vocabulary ◽  
Genetic Influences ◽  
Childhood And Adolescence ◽  
Language And Literacy

AbstractThe heritability of language and literacy skills increases during development. The underlying mechanisms are little understood, and may involve (i) the amplification of early genetic influences and/or (ii) the emergence of novel genetic factors (innovation). Here, we use multivariate structural equation models to quantify these processes, as captured by genome-wide genetic markers. Studying expressive and receptive vocabulary at 38 months and subsequent language, literacy and cognitive skills (7-13 years) in unrelated children (ALSPAC: N≤6,092), we found little support for genetic innovation during mid-childhood and adolescence. Instead, genetic factors for early vocabulary, especially those unique to receptive skills, were amplified. Explaining as little as 3.9%(SE=1.8%) variation in early language, the same genetic influences accounted for 25.7%(SE=6.4%) to 45.1%(SE=7.6%) variation in verbal intelligence and literacy skills, but also performance intelligence, capturing the majority of SNP-heritability (≤99%). This suggests that complex verbal and non-verbal cognitive skills originate developmentaly in early receptive language.

Easy Statistical Mediation Analysis With Distinguishable Dyadic Data

2019 ◽  
Vol 69 (6) ◽  
pp. 612-649 ◽  
Author(s):  
Jacob J Coutts ◽  
Andrew F Hayes ◽  
Tao Jiang
Keyword(s):  
Mediation Analysis ◽  
Indirect Effects ◽  
Structural Equation ◽  
Mutual Influence ◽  
Ordinary Least Squares ◽  
Equation Modeling ◽  
Least Squares Regression ◽  
Dyadic Data ◽  
Actor Partner Interdependence Model ◽  
Statistical Mediation Analysis

Abstract Research in communication and other social science disciplines that relies on measuring each member of a dyad on putative causes and effects can require complex analyses to illuminate how members of the dyad influence one another. Dyadic mediation analysis is a branch of mediation analysis that focuses on establishing the mechanism(s) by which mutual influence operates. Relying on the similarity between dyadic mediation analysis using structural equation modeling and mediation analysis with ordinary least squares regression, we developed MEDYAD, an easy-to-use computational tool for SPSS, SAS, and R that conducts dyadic mediation analysis with distinguishable dyadic data. MEDYAD implements the Actor-Partner Interdependence Model Extended to Mediation (APIMeM), as well as simpler and more complex dyadic mediation models. Bootstrapping methods are implemented for inferences about indirect effects. Additional features include methods for conducting all possible pairwise comparisons between indirect effects, heteroskedasticity-robust inference, and saving bootstrap estimates of parameters for further analysis.

Resource complementarity, transformative capacity, and inbound open innovation

2015 ◽  
Vol 30 (7) ◽  
pp. 842-854 ◽  
Author(s):  
Hao-Chen Huang ◽  
Mei-Chi Lai ◽  
Wei-Wei Huang
Keyword(s):  
Open Innovation ◽  
Structural Equation ◽  
Measurement Model ◽  
Ordinary Least Squares ◽  
Equation Modeling ◽  
Least Squares Regression ◽  
Content Type ◽  
Transformative Capacity ◽  
Resource Complementarity ◽  
Complementary Resources

Purpose – This study aims to examine the potential impact of external complementary resources on inbound open innovation and whether transformative capacity acts as a mediator in the process. If small and medium enterprises (SMEs) are to successfully implement inbound open innovation, they require injections of external complementary resources. Design/methodology/approach – Structural equation modeling was used to conduct confirmatory factor analysis to evaluate measurement model, while ordinary least squares regression analysis was used to test the hypotheses; research data are collected using surveys of 200 Taiwanese-owned SMEs in mainland China. Findings – Empirical results indicate that when SMEs seek to implement inbound open innovation, technological complementarity is the most important factor in resource complementarity. In addition, transformative capacity has a significant mediating role on the relationship between resource complementarity and inbound open innovation. Originality/value – The contribution of this paper lies in explaining the role played by transformative capacity in the process of inbound open innovation for SMEs through empirical analysis.

scholarly journals Development of ADHD symptoms in preschool children: Genetic and environmental contributions

2018 ◽  
Vol 31 (04) ◽  
pp. 1299-1305 ◽  
Author(s):  
Espen Moen Eilertsen ◽  
Line C. Gjerde ◽  
Kenneth S. Kendler ◽  
Espen Røysamb ◽  
Steven H. Aggen ◽  
...  
Keyword(s):  
Preschool Children ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Genetic Correlations ◽  
Population Based ◽  
Genetic Influences ◽  
Adhd Symptoms ◽  
Hyperactivity Disorder ◽  
Mother And Child ◽  
Specific Factors

AbstractWe examined genetic and environmental contributions to the development of symptoms of attention-deficit/hyperactivity disorder (ADHD) in preschool children. ADHD symptoms in siblings at 1.5, 3, and 5 years of age were investigated in a population-based sample from the prospective Norwegian Mother and Child Cohort Study. The longitudinal contributions of additive genetic, shared, twin-specific, and unique environmental influences were estimated using biometric structural equation models. Heritability of ADHD symptoms ranged from 54% to 70%. There was evidence of partially new genetic influences at successive ages, with genetic correlations ranging from .58 to .89. Contributions from shared environmental factors and twin-specific factors were minor. The importance of unique environmental effects appeared to increase across ages, and was mostly specific to a given age. There was no evidence suggesting that this pattern differs across males and females. Symptoms of ADHD are highly heritability in young children from as early as 1.5 years of age. Longitudinal stability of ADHD symptoms is mainly attributable to genetic influences, but there is also some evidence for age-specific genetic influences. These findings contribute to our understanding of development of ADHD early in life, and can guide future molecular genetics studies.

scholarly journals Conceptual replication of Seo (2008), “Self-efficacy as a mediator in the relationship between self-oriented perfectionism and academic procrastination”

2020 ◽  
Author(s):  
Matt Williams ◽  
Shoni Marshall-Edwards
Keyword(s):  
Self Efficacy ◽  
Structural Equation ◽  
Survey Design ◽  
Negative Relationship ◽  
Ordinary Least Squares ◽  
Academic Procrastination ◽  
Least Squares Regression ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Academic Tasks

Self-oriented perfectionism is the tendency to set high standards for oneself and evaluate one’s behaviour accordingly. Based on a study of 792 students in Korea, Seo (2008) reported finding a negative relationship between self-oriented perfectionism and academic procrastination—i.e., the tendency to procrastinate on academic tasks. Furthermore, Seo found that this relationship was completely mediated by self-efficacy. Seo’s study has been influential in the literature but has not been independently replicated. In this study we report a conceptual replication utilising 575 students from OECD countries and a cross-sectional survey design. A detailed preregistration (including data processing and analysis syntax) was lodged in advance of data collection at https://osf.io/xfvd8. Both ordinary least squares regression and structural equation modelling were used to test hypotheses. We found no evidence of a bivariate relationship between self-oriented perfectionism academic procrastination in either set of analyses, meaning that we were unable to reproduce one of Seo’s two key findings. However, we did find evidence of a small and negative indirect effect of self-oriented perfectionism on academic procrastination via self-efficacy, reproducing part of the mediation model reported by Seo.

What drives people to participate in online firestorms?

2020 ◽  
Vol 44 (3) ◽  
pp. 563-581
Author(s):  
Maria Gruber ◽  
Christiane Mayer ◽  
Sabine A. Einwiller
Keyword(s):  
Structural Equation ◽  
Design Methodology ◽  
Online Survey ◽  
Online Communication ◽  
Ordinary Least Squares ◽  
Equation Modeling ◽  
Least Squares Regression ◽  
Content Type ◽  
Collective Actors ◽  
Communication Environments

PurposeSocial media empower individuals to voice their opinions about issues that they perceive to be unacceptable. When many others add their opinions and large quantities of messages containing negative word-of-mouth suddenly spread online, an online firestorm occurs. By extending the situational theory of problem solving (Kim and Grunig, 2011) into the domain of online communication, this study aims to identify the drivers for participating in online firestorms.Design/methodology/approachWith reference to a fictitious online firestorm trigger (i.e. perceived moral misconduct) posted on Facebook, a qualitative pre-study and quantitative online survey were conducted. Based on the responses of 410 participants, an ordinary least squares regression was modeled to examine the factors of participating in the online firestorm. Later, structural equation modeling was applied to test the model and gauge its fit with the data.FindingsParticipants' involvement recognition, perception of being collective actors and approval of slacktivism behaviors positively predicted their participation in the online firestorm, whereas non-anonymity hampered it.Originality/valueThe study's findings not only contribute to the current understandings of online firestorms but are also valuable for developing theory and forms of professional crisis management. Moreover, they offer insights into the factors of online communication environments that encourage users to voice their opinions.

Measuring the Big Five in Self-Report and Other Ratings

2000 ◽  
Vol 16 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Claudio Barbaranelli ◽  
Gian Vittorio Caprara
Keyword(s):  
Big Five ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Error Variance ◽  
The Self ◽  
Self Report ◽  
Sources Of Information ◽  
Third Person ◽  
Fit Indexes ◽  
Response Modes

Summary: The aim of the study is to assess the construct validity of two different measures of the Big Five, matching two “response modes” (phrase-questionnaire and list of adjectives) and two sources of information or raters (self-report and other ratings). Two-hundred subjects, equally divided in males and females, were administered the self-report versions of the Big Five Questionnaire (BFQ) and the Big Five Observer (BFO), a list of bipolar pairs of adjectives ( Caprara, Barbaranelli, & Borgogni, 1993 , 1994 ). Every subject was rated by six acquaintances, then aggregated by means of the same instruments used for the self-report, but worded in a third-person format. The multitrait-multimethod matrix derived from these measures was then analyzed via Structural Equation Models according to the criteria proposed by Widaman (1985) , Marsh (1989) , and Bagozzi (1994) . In particular, four different models were compared. While the global fit indexes of the models were only moderate, convergent and discriminant validities were clearly supported, and method and error variance were moderate or low.

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